The present disclosure relates to image processing for recognizing text within images.
Digital images can include a wide variety of content. For example, digital images can illustrate landscapes, people, urban scenes, and other objects. Digital images often include text. Digital images can be captured, for example, using cameras or digital video recorders.
Image text (i.e., text in an image) typically includes text of varying size, orientation, and typeface. Text in a digital image derived, for example, from an urban scene (e.g., a city street scene) often provides information about the displayed scene or location. A typical street scene includes, for example, text as part of street signs, building names, address numbers, and window signs.
An example street scene 100 is shown in FIG. 1. Street scene 100 includes textual elements such as logo text 102 on an automobile as well as building signs 104 and 106. Text found within images can identify address locations, business names, and other information associated with the illustrated content.
The text within images can be difficult to automatically identify and recognize due both to problems with image quality and environmental factors associated with the image. Low image quality is produced, for example, by low resolution, image distortions, and compression artifacts. Environmental factors include, for example, text distance and size, shadowing and other contrast effects, foreground obstructions, and effects caused by inclement weather.